Introduction to Julia: Automatic differentiation with dual numbers Published 2020-11-15 Download video MP4 360p Recommendations 38:14 Pytorch tutorial: Collaborative filtering 40:32 Algorithmic Differentiation 1 26:48 Dual complex numbers and Leibniz's differentiation rules | Famous Math Problems 22b | N J Wildberger 09:44 Jacobian-vector product (Jvp) with ForwardDiff.jl in Julia 30:17 A hiring manager's perspective on succeeding in today's job market 08:29 Google Data Center 360° Tour 19:14 The strange cousin of the complex numbers -- the dual numbers. 28:08 Snake learns with NEUROEVOLUTION (implementing NEAT from scratch in C++) 24:22 Pytorch tutorial: Autoencoders 45:14 Сучасна або квантова картина світу. Лекція з курсу "Науковий образ світу". 06:01 Tutorial on Automatic Differentiation 11:24 Automatic Differentiation in 10 minutes with Julia 26:29 Deep Learning on Graphs(1/3): Node embedding 43:22 adressage1 9 1:22:11 Complex number fundamentals | Ep. 3 Lockdown live math 32:48 Pytorch tutorial: Convolutional neural network 15:55 How to organize your notes in Obsidian // The LATCH method Similar videos 36:02 Lecture 5 Part 2: Forward Automatic Differentiation via Dual Numbers 14:25 What is Automatic Differentiation? 10:12 Simple forward-mode AD in Julia using Dual Numbers and Operator Overloading 09:15 The Dual Numbers 47:39 6.1 Optimization Method - Automatic Differentiation 03:11 First introduction of dual numbers 32:36 Automatic Differentiation Techniques Used in JuMP | Miles Lubin | JuliaCon 2016 08:11 Automatic Differentiation for Solid Mechanics in Julia | Andrea Vigliotti | JuliaCon 2022 24:00 Fast Forward and Reverse-Mode Differentiation via Enzyme.jl | Many speakers | JuliaCon 2022 25:26 1.4. Automatic Derivation with Dual Numbers 25:33 [08x06] Calculus using Julia Automatic Differentiation | ForwardDiff.jl, ReverseDiff.jl and Pluto 09:11 Automatic Differentiation in Julia with ForwardDiff.jl More results